Millions of dollars and countless hours are spent reading through legal contracts by junior level attorneys, often error-prone due to stress and overwork. In order to help address this problem, we aim to create a Natural Language Processing (NLP) based contract analysis model using the FlairNLP framework trained using the Contract Understanding Atticus Dataset (CUAD) and legal word embeddings. The model will be tested for accuracy using 10 of the 41 labels in the CUAD dataset.